NNA: Dynamic Vehicle-Terrain Modeling and Control of Lightweight Ground Robots in Snow and Sand

该研究项目旨在从根本上了解轮式车辆在雪地和沙地等柔软地形中行驶的动力学。该项目将推导出运动模型，其中包括对车轮和地面之间相互作用的改进描述。这些创新的模型将允许处理，例如，轻型车辆和容易破碎的地形。这些模型将使机器人能够预测何时会出现可避免的卡住危险。新的基于模型的控制技术将允许机器人避免这种危险，例如，通过反复压实地形，适当调节牵引负载的缆绳力，或者简单地修改计划路线。研究结果将部署在移动的地面机器人系统中，这些机器人系统能够在无人看管的情况下穿越北极地区，携带或拖曳传感器包，以提供“地面实况”数据，用于与卫星或飞机测量结果进行比较。目前还没有一种轻型的自主移动的平台可以长时间自主地在北极地区漫游，而不会被低凝聚力的雪所固定。该项目建立在研究者成功使用类似机器人在南极更均匀和可预测的地形的基础上。该项目通过对北极地区进行长距离、长时间的科学调查，促进国家健康、繁荣和福利，这将有助于更好地了解北极系统对自然和人类活动的反应。该项目还支持NSF关于导航新北极的大想法。最后，该项目将支持达特茅斯大学本科生跨学科工程设计经验的新内容，并将为来自美国、丹麦和格陵兰岛的高中生的北极科学实践推广计划提供新材料。现有的车辆-地形模型已经推导并验证了重型车辆，并且已经表明轻型车辆的行为与这些模型预测的不同。因此，很难预测轻量级机器人的行为，在低流动性条件下，使用当前的模型。该项目的目标是为轻型地面机器人开发车辆-地形模型，其中包括所有重要的动力学，并将这些模型与车辆设计和控制相结合，以最大限度地提高机动性。 该项目将制定估计方法，以发现初期固定情况，并制定控制方法，通过改变地形避免固定。的剪切应力能力和调制拖载。将开发一个模块化机器人平台，以获取数据，用于推导和验证轻型机器人模型的车辆-地形模型和控制方法。该平台将允许快速修改车轮/履带板几何形状、地面压力和牵引杆载荷，以获得现场参数数据。高保真车辆-地形模型使控制方案包括基于模型的初期制动预测，触发控制模式，以避免制动，并使机器人能够通过软地形前进。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

This research project seeks fundamental understanding of the dynamics of wheeled vehicles moving through soft terrain such as snow and sand. The project will derive models of movement that incorporate improved descriptions of interactions between the wheels and the ground. These innovative models will allow the treatment of, for example, lightweight vehicles and easily crumbled terrain. These models will allow the robot to predict when it is in danger of getting irrevocably stuck. New model-based control techniques will then allow the robot to avoid this danger, for example, by repeated compaction of the terrain, appropriate modulation of cable forces from a towed load, or simply revising the planned route. The results will be deployed in mobile ground robot systems capable of traversing Arctic regions untended, carrying or towing sensor packages to provide "ground truth" data for comparison to satellite or aircraft measurements. No lightweight autonomous mobile platform currently exists that can roam Arctic terrain autonomously for long periods of time, without becoming immobilized by pockets of low cohesion snow. This project builds upon the Investigator's success with similar robots used in the more uniform and predictable terrain of the Antarctic. This project advances the national health, prosperity, and welfare by enabling long-range, long-duration scientific surveys of the Arctic region, that will provide improved understanding of the response of Arctic systems to natural and human activity. This project also supports the NSF Big Idea on Navigating the New Arctic. Finally, the project will support new content in the interdisciplinary engineering design experience for Dartmouth undergraduates, and will provide new material to a hands-on Arctic science outreach program for high school students from the US, Denmark, and Greenland.Existing vehicle-terrain models have been derived and validated for heavy vehicles, and it has been shown that the behavior of lightweight vehicles differs from what these models predict. As a result, it is difficult to anticipate lightweight robot behavior in low mobility conditions using current models. The goal of this project is to develop vehicle-terrain models for lightweight ground robots that includes all the important dynamics, and integrates those models with vehicle design and control to maximize mobility. The project will develop estimation methods to detect incipient immobilization and control methods to avoid immobilization by reshaping the terrain?s shear stress capacity and modulating towed load. A modular robotic platform will be developed to acquire data for deriving and validating vehicle-terrain models and control approaches for lightweight robot models. The platform will allow rapid modification of wheel/grouser geometry, ground pressure, and drawbar load to obtain parametric data in situ. Higher fidelity vehicle-terrain models enable control schemes comprised of model-based prediction of incipient immobilization that trigger control modes to avoid immobilization and enable a robot to make forward progress through soft terrain.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.